Meet the Instructors

Antoine Flahault

Professor of Public Health and Director of the Institute of Global Health (Faculty of Medicine, University of Geneva) and co-Director of Centre Virchow-Villermé (Université Paris Descartes)University of Geneva and Université Paris Descartes – Sorbonne Paris Cité

Rafael Ruiz De Castañeda

Institute of Global Health - Faculty of MedicineUniversity of Geneva

Defeating Ebola Together Week 3: Ebola's Impact
"Big Data"

The issue of monitoring systems

has greatly evolved over the past few years, and we

are going to look at how these changes have impacted Ebola.

As of today, we have traditional monitoring systems,

which we might refer to as reportable disease systems,

or mandatory notification systems.

Most of the time, doctors are the ones doing the reporting.

Once doctors notify public authorities and health agencies,

the latter notify the national government, which then, in partnership with the WHO, tries

to collect all the relevant data and distribute it.

That's the traditional system.

Today, however, we have an enormous wealth of health-related information

and a certain number of systems aiming to capture all this information,

sometimes referred to as "Big Data" -- the massive amount of data surrounding us and produced by a wide variety of sources.

Big Data can come from tweets, or blogs,

or press clippings -- anything that's online.

Certain tools, for instance, capture the

searches and queries made on search engines like Google.

One such tool, called Google Flu Trends, tries to capture

any signal that may indicate a flu epidemic.

When people have the flu, they might google words

related to antipyretics, such as "paracetamol," or

they might google the word "fever,"

or they might enter various queries

suggestive of what may be a flu epidemic.

Is it possible to use this type of

data-driven tool for Ebola?

Were any such tools used in the case of Ebola, and were they

more effective in terms of early detection than

the traditional reporting systems administered by the State?

Interestingly, there is a tool called Harvard Health Map

which claims to be capable of

searching the entire internet for press clippings, blogs, etc.

-- particularly very informal or unofficial sources of information.

This information is in no way validated or rigorous

from an epidemiological standpoint, nor is it

accredited by the World Health Organization or any government.

It's truly informal information.

Harvard Health Map attempts to

collect and explore this data

and translate it into maps.

Was it able to produce an early warning?

Yes, at least that is what Harvard Health Map has claimed, since

it was able on March 14, 2014 to

declare the presence of an epidemic that might be Ebola in West Africa, in Guinea specifically.

Harvard Health Map

issued this statement nine days before the World Health Organization's

official announcement of an epidemic in Guinea.

So yes, nine days earlier.

Does that mean that this tool, which for the first time ever (or almost)

was able to issue an early warning based on Big Data,

is going to become the primary or dominant tool?

It's hard to say because when you look back, it turns out

that one day earlier, on March 13th, a press agency called Xinhua had announced -- in French --

that a mysterious fever had killed eight people in Macenta, Guinea.

Why was this press agency able to make such an announcement before Harvard Health Map's?

Because the chief disease prevention officer of the Guinean government, Dr Sakobo Keita,

had held a very official press conference

during which he announced that Macenta

was home to a mysterious fever, the origins of which were unknown,

that eight people had died and that this could be an outbreak of

some as yet unidentified hemorrhagic fever --

perhaps SARS, perhaps the Marburg virus. As it turns out, it was Ebola.

So early warning signals are very important.

An epidemic is like a forest fire:

if you react early enough, all you need is a single bucket of water;

but if you waste time, every minute counts, and very soon

you need to call in the fire department, and then firefighting aircraft.

An epidemic is a similar situation:

outbreaks spread exponentially and very fast, so early warnings

are absolutely essential.

As we know, such epidemics quickly become uncontrollable,

so receiving signals very early on, even preliminary signals

with little confirmation, is extremely valuable.

An early warning is priceless -- I'd go so far as to say that even a false alarm is

better than no information, because it's better to look back and

realize things weren't as bad as expected than to

react too late, which leads to very harmful consequences.

As of today, one issue associated with

tools that sift through Big Data is that they do not necessarily

account for the fact that everyone does not speak English.

Software tools such as Harvard Health Map

mainly search through information written in English.

Because of the need to translate, an entire day was lost

between the press conference held in Guinea, in French, and

the English translations picked up by the Boston-based tool on blogs, etc.